Simultaneously Increasing Profit and Reducing Emissions Through Process Optimization for Integrated Petrochemical Plants

Source: AIChE
  • Type:
    Conference Presentation
  • Conference Type:
    AIChE Annual Meeting
  • Presentation Date:
    October 18, 2011
  • Duration:
    30 minutes
  • Skill Level:
  • PDHs:

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Refineries and petrochemical plants are leading segment of the entire chemical process industry. It was reported that the value of the product shipments by refineries in U.S. accounted for 9.32% of the entire manufacturing sector of the U.S. economy in 2007. On the other hand, air emissions from refineries and petrochemical plants are significant. The carbon dioxide (CO2) emissions from refineries account for about 4% of the global CO2 emissions, close to 1 billion tons of CO2 per year. Due to an increasing concern, specific policies for refinery emission control have been enacted, and these emission control polices will heavily affect U.S. petroleum refineries.

When an emission reduction strategy is implemented in a petrochemical plant, it most likely causes more conservative design and operations, and requires higher capital investment and manufacturing costs. However, emissions in a petrochemical plant generally mean the loss of raw materials and energy which could supposedly generate products. Thus, emission reduction may possibly bring opportunities for the plant profit increment. In this paper, a process optimization model and a methodology were developed, which enabled profitable emission reduction (PER).

The model includes major facilities of refinery and petrochemical plants. For each facility model, certain simplifications are made to reduce the model complexity, and meanwhile, keep the model accuracy. Facility models include material balance equations, property correlations, capacity constraints, and utility consumption correlations. Facility models are tuned and validated with actual operating data.

The model is a multi-objective mixed-integer nonlinear programming (MINLP) model. The integer variables and constraints enable the model to optimize both process flowsheet and operating parameters. The objective functions include profit, energy consumption, carbon dioxide (CO2) emission, volatile organic compounds (VOC), and nitrogen oxides (NOX). Pareto frontier method is employed to show relations of these objective functions. Optimization results give PER (profitable emissions reduction) region for various production schemes. When production schemes are in the PER region, the optimized flowsheet can reduce the CO2, VOC and NOX emissions by 10%, as well as increase operating profit by 4%.

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